This book is motivated by the apparent gap between the widespread usage of multiples in valuation practice and the deficiency of relevant research related to multiples. While valuing firms using multiples seems straightforward on the surface, it actually invokes several complications and open issues. To close this gap, the book examines the role of multiples in equity valuation and transforms the standard multiples valuation method into a comprehensive framework for using multiples in equity valuation.

To identify the underlying drivers of different multiples, I derive intrinsic multiples from fundamental equity valuation models. An overview of common market multiples and the standard multiples valuation method including its criticism initiates an in-depth analysis of every single step of the four-step multiples valuation process. I investigate key criteria for the selection of value relevant measures and for the identification of comparable firms, and assess the usefulness of a two-factor multiples valuation model combining book value and earnings multiples from a theoretical point of view.

In the empirical study, I find that multiples generally approximate market values reasonably well. In terms of relative performance, the results show that: (1) equity value multiples outperform entity value multiples; (2) knowledge-related multiples outperform traditional multiples in science-based industries; and (3) forward-looking multiples, in particular the two-year forward-looking P/E multiple, outperform trailing multiples. For the selection of comparable firms, the results suggest the use of a preferably fine industry definition. While I find support for the general perception that different industries are associated with different best multiples among trailing multiples, including forecast material reveals a clear dominance of the two-year forward-looking P/E multiple across industries. The results of the analysis of the properties and valuation accuracy of the two-factor multiples valuation model provide evidence for the theoretical reasoning that the usefulness of in-corporating the P/B multiple as a second decision relevant multiple into the two-factor model depends on: (1) its valuation accuracy in a specific industry; and (2) the exclusiveness of information provided over the first decision relevant multiple.